Superradiant Emission from Coherent Excitons in van Der Waals Heterostructures

Recent advancements in isolation and stacking of layered van der Waals materials have created an unprecedented paradigm for demonstrating varieties of 2D quantum materials. Rationally designed van der Waals heterostructures composed of monolayer transition-metal dichalcogenides (TMDs) and few-layer hBN show several unique optoelectronic features driven by correlations. However, entangled superradiant excitonic species in such systems have not been observed before. In this report, it is demonstrated that strong suppression of phonon population at low temperature results in a formation of a coherent excitonic-dipoles ensemble in the heterostructure, and the collective oscillation of those dipoles stimulates a robust phase synchronized ultra-narrow band superradiant emission even at extremely low pumping intensity. Such emitters are in high demand for a multitude of applications, including fundamental research on many-body correlations and other state-of-the-art technologies. This timely demonstration paves the way for further exploration of ultralow-threshold quantum-emitting devices with unmatched design freedom and spectral tunability.     

Fast internal dynamics in polyelectrolyte gels measured by dynamic light scattering

Summary Dynamic light scattering was used to investigate the dynamics of sodium poly(styrene sulfonate) and fully neutralized poly(acrylic acid) gels as a function of the degree of swelling and weight ratio of cross-linking agent. It was shown that the collective diffusion coefficient increases with increasing degree of swelling and that the diffusion coefficient shows stronger concentration dependence than predicted by scaling arguments. For gel samples measured at the swelling equilibrium, the diffusion coefficient increases with increasing gel concentration for both gel systems.     

Modeling tool wear in end-milling using enhanced GMDH learning networks

This paper presents an enhanced approach to predictive modeling for determining tool-wear in end-milling operations based on enhanced-group method of data handling (e-GMDH). Using milling input parameters (speed, feed, and depth-of-cut) and response (tool wear), the data for the model is partitioned into training and testing datasets, and the training dataset is used to realize a predictive model that is a function of the input parameters and the coefficients determined. In our approach, we first present a methodology for modeling, and then develop predictive model(s) of the problem being solved in the form of second-order equations based on the input data and coefficients realized. This approach leads to some generalization because it becomes possible to predict not only the test data obtained during experimentation, but other test data outside the experimental results can also be used. Moreover, this approach makes it easy to present the realized solution in a form that can be further optimized for the input parameters using some optimization techniques. The results realized using our e-GMDH method are promising, and the comparative study presented shows that the e-GMDH outperforms polynomial neural network (PNN); moreover, it is more flexible than the conventional GMDH, which tends to produce nonlinear solutions even for simple problems. In the investigation, the extended particle swarm optimization (PSO) technique was applied to obtain the optimal parameters. Consequently, the modeling approach is extremely useful in realizing a computer-aided process-planning system in an advanced manufacturing environment.     

Hemorrhagic fever with renal syndrome

The authors describe the illness of a Czech soldier who while serving in the UNPROFOR forces in an area with the endemic occurrence of hantaviruses became infected with this agent and developed haemorrhagic fever with renal syndrome. The severe clinical course which called for seven haemodialyzation procedures led to the patient's recovery. The authors describe the course of the disease and epidemiological circumstances.     

Rotating magnetic field-driven flows in conductive inhomogeneous media: Part I—Numerical study

This paper presents a numerical study of the Lorentz force and fluid flow induced by a rotating magnetic field in a medium with a nonhomogeneous electric conductivity placed in a cylindrical vessel with insulated walls. The nonhomogeneity is modeled by the presence of a solid and a liquid phase of different electrical conductivity. The solid phase is located orthogonally to the axis of rotation, which corresponds to the case of unidirectional solidification. The simulations were performed for different locations of the solid front and different ratios of the electrical conductivity, σ _s /σ _l =0.2... 10. Here σ _s and σ _l are the electric conductivity of the solid and liquid phases, respectively. The results showed that the difference between electrical conductivity of solid and liquid phases has a noticeable effect on the mean-time Lorentz force and the velocity: namely, the presence of the solid phase (σ _s >σ _l ) leads to an increase of the Lorentz force and fluid flow in the cylinder.     

Using spreadsheets in introductory EE courses

Ways in which spreadsheet programs can be used to introduce practical considerations in introductory electrical engineering courses are discussed. Examples are presented which show that spreadsheets can be used to predict and/or minimize the errors due to loading, the availability of only standard resistor values, and resistor tolerances. The circuits considered in these examples were selected to be as simple as possible. These examples could be used in the first semester of sophomore credits. They illustrate trade-offs, performance criteria, and nonunique solutions, and are intended to illustrate the power of spreadsheet programs. In the first example, a macro is used to implement a simple iterative optimization procedure. In the second example, minimization is done by exhaustive search using the table lookup capabilities of the spreadsheet. In the final example, the spreadsheet's random number generator is used to perform a Monte Carlo analysis